Prometheus exporter for Cisco Unified Computing System (UCS) Manager

Related tags

Deep Learningprometheus-ucs-exporter
Overview

prometheus-ucs-exporter

Overview

Use metrics from the UCS API to export relevant metrics to Prometheus

This repository is a fork of Drew Stinnett's original exporter at oit-ssi-systems/prometheus-ucs-exporter.

Modifications made include:

  • Added production server (FastAPI)
  • Added additional metrics
  • Added Grafana dashboard
  • Minor fixes and refactorings

Install the Grafana dashboard by importing the JSON file grafana/dashboard.json.

Cisco UCSM Grafana dashboard

Installation

Build and run with Docker:

docker build -t prometheus-ucs-exporter .

docker run -p 3001:3001 -e PORT=3001 \
-e PROM_UCS_USERNAME='ucs-mydomain\username' \
-e PROM_UCS_PASSWORD='passw0rd' \
prometheus-ucs-exporter

Fetch metrics:

curl http://localhost:3001/metrics?domain=my-domain.example.com

Note: Metrics are fetched in a background worker after an initial scrape, since UCSM can be slow to respond. Continue polling the /metrics endpoint until metrics are returned.

Usage

docker pull ghcr.io/marshallwace/prometheus-ucs-exporter:0.0.2

SPDX update

pip install --user pipx

pipx run reuse addheader --copyright "2022 Marshall Wace <[email protected]>" --license "GPL-3.0-only" *.py
You might also like...
Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

NuPIC Numenta Platform for Intelligent Computing The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implem

Numenta 6.2k Feb 12, 2021
xitorch: differentiable scientific computing library

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

null 24 Apr 15, 2021
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

Google Research 258 Dec 29, 2022
Blender scripts for computing geodesic distance
Blender scripts for computing geodesic distance

GeoDoodle Geodesic distance computation for Blender meshes Table of Contents Overivew Usage Implementation Overview This addon provides an operator fo

null 20 Jun 8, 2022
Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

Liang HUANG 87 Dec 28, 2022
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

Filippo Bianchi 249 Dec 21, 2022
Material related to the Principles of Cloud Computing course.

CloudComputingCourse Material related to the Principles of Cloud Computing course. This repository comprises material that I use to teach my Principle

Aniruddha Gokhale 15 Dec 2, 2022
Code for the paper "Next Generation Reservoir Computing"

Next Generation Reservoir Computing This is the code for the results and figures in our paper "Next Generation Reservoir Computing". They are written

OSU QuantInfo Lab 105 Dec 20, 2022
Differentiable scientific computing library

xitorch: differentiable scientific computing library xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely

null 98 Dec 26, 2022
Comments
  • How to support polling multiple UCS Domains

    How to support polling multiple UCS Domains

    Is it possible to support polling of multiple UCS domains using a single prometheus instance or is it better to dedicate a prmetheus container to each UCS domain?

    opened by dwebr 1
  • UCS System returns

    UCS System returns "not-applicable" for kernel_mem_total and kernel_mem_free stats

    Issue: UCS running version 4.2(1m)B returns "not-applicable" for kernel_mem_total and kernel_mem_free stats which results in prometheus throwing errors during polling.

    Work around: comment out the following statements in the swsystem.py file.

    kernel_mem_total.labels(self.domain, switch).set(int(item.kernel_mem_total))
kernel_mem_free.labels(self.domain, switch).set(int(item.kernel_mem_free))

    Example Output

    /repos/prometheus-ucs-exporter/scripts$ ./explore.py query-classid swSystemStats

Managed Object                  :       SwSystemStats
--------------
class_id                        :SwSystemStats
child_action                    :None
correctable_parity_error        :not-applicable
correctable_parity_error_avg    :not-applicable
correctable_parity_error_max    :not-applicable
correctable_parity_error_min    :not-applicable
dn                              :sys/switch-B/sysstats
intervals                       :58982460
kernel_mem_free                 :not-applicable
kernel_mem_free_avg             :not-applicable
kernel_mem_free_max             :not-applicable
kernel_mem_free_min             :not-applicable
kernel_mem_total                :not-applicable
kernel_mem_total_avg            :not-applicable
kernel_mem_total_max            :not-applicable
kernel_mem_total_min            :not-applicable
load                            :2.360000
load_avg                        :2.413333
load_max                        :2.620000
load_min                        :2.130000
mem_available                   :52264
mem_available_avg               :52278
mem_available_max               :52302
mem_available_min               :52264
mem_cached                      :11591
mem_cached_avg                  :11576
mem_cached_max                  :11591
mem_cached_min                  :11563
rn                              :sysstats
sacl                            :None
status                          :None
suspect                         :no
thresholded                     :
time_collected                  :2022-09-24T10:13:48.368
update                          :131081



Managed Object                  :       SwSystemStats
--------------
class_id                        :SwSystemStats
child_action                    :None
correctable_parity_error        :not-applicable
correctable_parity_error_avg    :not-applicable
correctable_parity_error_max    :not-applicable
correctable_parity_error_min    :not-applicable
dn                              :sys/switch-A/sysstats
intervals                       :58982460
kernel_mem_free                 :not-applicable
kernel_mem_free_avg             :not-applicable
kernel_mem_free_max             :not-applicable
kernel_mem_free_min             :not-applicable
kernel_mem_total                :not-applicable
kernel_mem_total_avg            :not-applicable
kernel_mem_total_max            :not-applicable
kernel_mem_total_min            :not-applicable
load                            :3.820000
load_avg                        :2.701667
load_max                        :3.820000
load_min                        :2.090000
mem_available                   :52062
mem_available_avg               :52050
mem_available_max               :52062
mem_available_min               :52036
mem_cached                      :11060
mem_cached_avg                  :11068
mem_cached_max                  :11083
mem_cached_min                  :11060
rn                              :sysstats
sacl                            :None
status                          :None
suspect                         :no
thresholded                     :
time_collected                  :2022-09-24T10:14:32.366
update                          :131078
    bug 
    opened by dwebr 0
Releases(v0.0.2)
Owner
Marshall Wace
Marshall Wace
GitHub Repository
Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation

Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation The code of: Context Decoupling Augmentation for Weakly Supervised Semanti

54 Dec 12, 2022
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

Shiming Chen 6 Aug 16, 2022
Table-Extractor 表格抽取

(t)able-(ex)tractor 本项目旨在实现pdf表格抽取。 Models 版面分析模块（Yolo） 表格结构抽取（ResNet + Transformer） 文字识别模块（CRNN + CTC Loss） Acknowledgements TableMaster attention-i

2 Jan 15, 2022
Adversarial-autoencoders - Tensorflow implementation of Adversarial Autoencoders

Adversarial Autoencoders (AAE) Tensorflow implementation of Adversarial Autoencoders (ICLR 2016) Similar to variational autoencoder (VAE), AAE imposes

Qian Ge 236 Nov 13, 2022
High-Resolution Image Synthesis with Latent Diffusion Models

Latent Diffusion Models arXiv | BibTeX High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach*, Andreas Blattmann*, Dominik Lorenz

CompVis Heidelberg 5.6k Dec 30, 2022
Bunch of different tools which helps visualizing and annotating images for semantic/instance segmentation tasks

Data Framework for Semantic/Instance Segmentation Bunch of different tools which helps visualizing, transforming and annotating images for semantic/in

Bruno Fernandes Carvalho 5 Dec 21, 2022
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

Meta Research 141 Jan 07, 2023
The implementation of ICASSP 2020 paper "Pixel-level self-paced learning for super-resolution"

Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti

Elon Lin 41 Dec 15, 2022
Simple, efficient and flexible vision toolbox for mxnet framework.

MXbox: Simple, efficient and flexible vision toolbox for mxnet framework. MXbox is a toolbox aiming to provide a general and simple interface for visi

Ligeng Zhu 31 Oct 19, 2019
🐦 Quickly annotate data from the comfort of your Jupyter notebook

🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort

Anastasis Germanidis 647 Jan 05, 2023
Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion"

DSPoint Official pytorch implementation of "DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion" Coming soon, as soon as I finish a

Ziyao Zeng 14 Feb 26, 2022
Python parser for DTED data.

DTED Parser This is a package written in pure python (with help from numpy) to parse and investigate Digital Terrain Elevation Data (DTED) files. This

Ben Bonenfant 12 Dec 18, 2022
Main repository for the HackBio'2021 Virtual Internship Experience for #Team-Greider ❤️

Hello 🤟 #Team-Greider The team of 20 people for HackBio'2021 Virtual Bioinformatics Internship 💝 🖨️ 👨‍💻 HackBio: https://thehackbio.com 💬 Ask us

Siddhant Sharma 7 Oct 20, 2022
Replication package for the manuscript "Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?" submitted to TOSEM

tosem2021-personality-rep-package Replication package for the manuscript "Using Personality Detection Tools for Software Engineering Research: How Far

Collaborative Development Group 1 Dec 13, 2021
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions"

TEMOS: TExt to MOtionS Generating diverse human motions from textual descriptions Description Official PyTorch implementation of the paper "TEMOS: Gen

Mathis Petrovich 187 Dec 27, 2022
Code repo for "FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation" (ICCV 2021)

FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation (ICCV 2021) This repository contains the implementation of th

Yuhang Zang 21 Dec 17, 2022
Example-custom-ml-block-keras - Custom Keras ML block example for Edge Impulse

Custom Keras ML block example for Edge Impulse This repository is an example on

Edge Impulse 8 Nov 02, 2022
Project dự đoán giá cổ phiếu bằng thuật toán LSTM gồm: code train và code demo

Web predicts stock prices using Long - Short Term Memory algorithm Give me some start please!!! User interface image: Choose: DayBegin, DayEnd, Stock

Vo Thuong Truong Nhon 8 Nov 11, 2022
CNNs for Sentence Classification in PyTorch

Introduction This is the implementation of Kim's Convolutional Neural Networks for Sentence Classification paper in PyTorch. Kim's implementation of t

Shawn Ng 956 Dec 19, 2022
Reliable probability face embeddings

ProbFace, arxiv This is a demo code of training and testing [ProbFace] using Tensorflow. ProbFace is a reliable Probabilistic Face Embeddging (PFE) me

Kaen Chan 34 Dec 31, 2022